Localized nonlinear functional equations and two sampling problems in signal processing

    Authors

    Q. Y. Sun

    Comments

    Authors: contact us about adding a copy of your work at STARS@ucf.edu

    Abbreviated Journal Title

    Adv. Comput. Math.

    Keywords

    Nonlinear functional equation; Strict monotonicity; Inverse-closedness; Banach algebra; Infinite matrix; Instantaneous companding; Average; sampling; Signal with finite rate of innovation; Shift-invariant space; SHIFT-INVARIANT SPACES; FINITE SECTION METHOD; OFF-DIAGONAL DECAY; INFINITE MATRICES; WIENERS LEMMA; PSEUDODIFFERENTIAL-OPERATORS; RECONSTRUCTING SIGNALS; BANACH-ALGEBRAS; INNOVATION; FRAMES; Mathematics, Applied

    Abstract

    Let 1 a parts per thousand currency sign p a parts per thousand currency sign a. In this paper, we consider solving a nonlinear functional equation f (x) = y, where x, y belong to a"" (p) and f has continuous bounded gradient in an inverse-closed subalgebra of a"not sign (a""(2)), the Banach algebra of all bounded linear operators on the Hilbert space a"" (2). We introduce strict monotonicity property for functions f on Banach spaces a"" (p) so that the above nonlinear functional equation is solvable and the solution x depends continuously on the given data y in a"" (p) . We show that the Van-Cittert iteration converges in a"" (p) with exponential rate and hence it could be used to locate the true solution of the above nonlinear functional equation. We apply the above theory to handle two problems in signal processing: nonlinear sampling termed with instantaneous companding and subsequently average sampling; and local identification of innovation positions and qualification of amplitudes of signals with finite rate of innovation.

    Journal Title

    Advances in Computational Mathematics

    Volume

    40

    Issue/Number

    2

    Publication Date

    1-1-2014

    Document Type

    Article

    Language

    English

    First Page

    415

    Last Page

    458

    WOS Identifier

    WOS:000334683300007

    ISSN

    1019-7168

    Share

    COinS